Integrated analysis of electrical stimulation effects on Pseudomonas aeruginosa PAO1 inoculated denitrifying community: targeted and untargeted metabolomic analysis of phenazine biosynthesis and quorum sensing

群体感应 铜绿假单胞菌 代谢途径 生物化学 代谢组学 吩嗪 生物合成 假交替单胞菌 生物 代谢物 绿脓素 吲哚试验 微生物学 化学 新陈代谢 细菌 毒力 基因 生物信息学 遗传学 16S核糖体RNA
作者
Wu Li,Yong Liu,Jianping Deng,Shuanglin Gui,Hanbing Nie
出处
期刊:Frontiers in Microbiology [Frontiers Media]
卷期号:16: 1621417-1621417 被引量:4
标识
DOI:10.3389/fmicb.2025.1621417
摘要

This study investigates how 0.8 V applied voltage modulates phenazine biosynthesis, quorum sensing (QS), and microbial interactions in Pseudomonas aeruginosa PAO1-inoculated microbial electrolysis cell (MEC) reactors. Voltage stimulation significantly enhanced phenazine derivatives (PYO: 8.65-fold; 1-OH-PHZ: 14.98-fold) and QS signals (C4-HSL: 2.88-fold; 3-OXO-C12-HSL: 2.21-fold), correlating with upregulated biosynthetic genes (phzG: 14.8-fold; rhlI: 15.2-fold). Electrical stimulation amplified QS cross-regulation, reinforcing Las-mediated positive feedback on Rhl/PQS systems while attenuating Rhl’s inhibition of PQS. Untargeted metabolomic analysis demonstrated significant alterations in bacterial metabolic activity under electrical stimulation, identifying 140 differential metabolites. Among these, indole, a signaling molecule with QS-like functionality, exhibited the highest VIP score as an upregulated metabolite, and another indole derivative, brassicanal A, was also elevated. KEGG pathway enrichment analysis highlighted that these metabolites were primarily associated with amino acid metabolism and transport, while anthranilic acid and L-tryptophan—key metabolites linked to both indole-related pathways and phenazine biosynthesis—were also identified. Correlation analysis between differential metabolites with microbial communities confirmed that Delftia and Burkholderiales were strongly associated with phenazine biosynthesis and QS activity in P. aeruginosa PAO1. These findings highlight voltage as a key driver of metabolic rewiring and microbial niche partitioning, optimizing MEC reactor performance for wastewater treatment. This work provides foundational insights into electro-stimulated biofilm engineering through targeted QS and metabolic pathway regulation.
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